Address comments

Author: avinashpancham

pandas/io/sql.py

@@ -485,10 +485,12 @@ def read_sql(
 
     Examples
     --------
-    Read data from SQL via either a SQL query or a SQL tablename (latter not
-    possible for SQLite tables)
+    Read data from SQL via either a SQL query or a SQL tablename.
+    When using a SQLite database only SQL queries are accepted,
+    providing only the SQL tablename will result in an error.
+
     >>> from sqlite3 import connect
-    >>> conn = connect('file.db')
+    >>> conn = connect(':memory:')
     >>> df = pd.DataFrame(data=[[0, '10/11/12'], [1, '12/11/10']],
     ...                   columns=['int_column', 'date_column'])
     >>> df.to_sql('test_data', conn)
@@ -500,12 +502,12 @@ def read_sql(
 
     >>> pd.read_sql('test_data', 'postgres:///db_name')  # doctest:+SKIP
 
-    Apply dateparsing to columns through the ``parse_dates`` argument
+    Apply date parsing to columns through the ``parse_dates`` argument
 
     >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
     ...             parse_dates=["date_column"])
-           int_column date_column
+       int_column date_column
     0           0  2012-10-11
     1           1  2010-12-11
 
@@ -517,11 +519,11 @@ def read_sql(
     >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
     ...             parse_dates={"date_column": {"errors": "ignore"}})
-           int_column date_column
+       int_column date_column
     0           0  2012-10-11
     1           1  2010-12-11
 
-    2. Apply a dayfirst dateparsing order on the values of "date_column"
+    2. Apply a dayfirst date parsing order on the values of "date_column"
 
     >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
@@ -530,12 +532,12 @@ def read_sql(
     0           0  2012-11-10
     1           1  2010-11-12
 
-    3. Apply custom formatting when dateparsing the values of "date_column"
+    3. Apply custom formatting when date parsing the values of "date_column"
 
     >>> pd.read_sql('SELECT int_column, date_column FROM test_data',
     ...             conn,
     ...             parse_dates={"date_column": {"format": "%d/%m/%y"}})
-           int_column date_column
+       int_column date_column
     0           0  2012-11-10
     1           1  2010-11-12
     """